1. Field of the Invention
The present invention is related to search system(s) including human-assisted search system(s), and more specifically related to assisting with search system operation(s) including improving utilization of resource(s) employed by a human assisted search system. A system and method whereby information conversion may be optimized utilizing a human assistant are described.
2. Description of the Related Art
In general search systems are keyword driven systems. Keywords included in a request for information may be used in various ways to index items such as URL's, advertisements, etc. which may be provided to a user responsive to a request for information. In order to perform an information search based on other types of information such as a spoken request, an image, a natural language request, or a request which requires translation, it may be desirable to convert information received as part of a request from one form to another. Software and systems have been developed to convert speech to text, to extract information from an image, to convert natural language queries into a form which may be more amenable to an automated search, to translate from a source language to a target language, etc. Technologies created by companies such as TellMe®, Nuance™, and Vlingo™ have been deployed to convert spoken information into text. Image recognition systems from companies such as Eyealike™, Esker®, etc. have been deployed in order to search images to associate keywords and/or tags with the images. Audio recognition systems such as Gracenote's Mobile MusicID™ system have been deployed to compare audio recordings to a database of known recordings.
These types of technologies have allowed automated conversion of information to find a large and growing marketplace. However, there are limitations associated with such systems. Without feedback, the systems and software are not able to progressively improve the system capability. In some instances, speaker dependent voice recognition has been found to be more effective than speaker independent voice recognition, but it may be burdensome for a user to provide feedback to the system. In particular, correction of errors may become annoying to a user, and may cause a low acceptance rate of the system by customers. There is no known system and method whereby a human assistant may be provided to improve utilization of a resource such as a recognition system, an interpretation system, a translation system, or other system which may benefit from information provided by a human assistant(s).
Many people would benefit from and appreciate automated systems for speech, image, music, and handwriting recognition, or speech synthesis, translation, etc. However, error rates of such systems may exceed a user tolerance level. Learning algorithms may reduce error rates over time, but a user may not tolerate the learning curve, or user dependent information may not be available to a resource performing a conversion process.
In light of this and other limitations, a scalable method and system for making a human assistant available to improve utilization of system resources would be greatly appreciated.